Bibliographic record
Abstract
Canada’s Drug Agency (CDA-AMC) recommends that Dupixent be reimbursed by public drug plans for the treatment of severe chronic rhinosinusitis with nasal polyposis (CRSwNP) if certain conditions are met. Dupixent should only be covered to treat adults with severe CRSwNP whose bilateral nasal polyps are confirmed endoscopically or by CT scan, who are tolerant and able to continue the use of intranasal corticosteroids (INCS) but have refractory symptoms despite use of an optimized INCS for at least 3 months, and who have persistent symptoms despite adequate recent treatment with systemic corticosteroids (SCS) and/or nasal polyp surgery. Dupixent should only be reimbursed if the patient is under the care of a physician with expertise in managing severe CRSwNP. When Dupixent is first prescribed, the physician must submit a baseline 22-item Sino-Nasal Outcome Test (SNOT-22) score or endoscopic Nasal Polyp Score (NPS) so that response to treatment can be measured. The cost of Dupixent should be reduced.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".